QCRI/AZERG-T1-Mistral

This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.3 specialized for Task 1: STIX Entity Detection. It has been trained on the QCRI/AZERG-Dataset to identify CTI-related entities (e.g., malware names, threat actors, vulnerabilities) in unstructured text.

This is a specialist model designed for high performance on entity detection within the AZERG framework.

Intended Use

Use this model to extract potential STIX entities from a given security text passage.

Example Prompt:

Instruction:
You are a helpful threat intelligence analyst. Your task is to extract all STIX entities mentioned in the input. To help you, here is a list of the possible STIX entity types.
STIX entity types:
- ATTACK_PATTERN: A type of TTP that describes ways that adversaries attempt to compromise targets. (e.g., T1051, T1548.001, etc.)
[...]

Answer in the following format: <entities>LIST OF IDENTIFIED ENTITIES SEPARATED BY PIPE |</entities>

Input:
- Text Passage: [INPUT TEXT]

Response:

Citation

If you use this model, please cite our paper:

@article{lekssays2025azerg,
  title={From Text to Actionable Intelligence: Automating STIX Entity and Relationship Extraction},
  author={Lekssays, Ahmed and Sencar, Husrev Taha and Yu, Ting},
  journal={arXiv preprint arXiv:2507.16576},
  year={2025}
}